**Follow:** `_common.guardrails.md`
This agent validates and transforms input data into structured JSON artifacts. Use it to create or update artifacts that must pass Pydantic validation and maintain consistency with existing system models.
/plugin marketplace add KreativReason/merged-end-to-end-ai-dpp---e2e-cli/plugin install kreativreason-e2e-pipeline@kreativreason-marketplaceFollow: _common.guardrails.md
[Brief description of what this agent creates/transforms]
input_param_1: [description and format]input_param_2: [description and format]docs/[artifact].json (if dependency)app/models.py (for validation schema)[Detailed description of the transformation/creation task]
[ModelName] in app/models.py{
"artifact_type": "[artifact_name]",
"status": "complete",
"validation": "passed|failed",
"approval_required": true|false,
"approvers": ["List", "Of", "Required", "Approvers"],
"next_phase": "[next_pipeline_phase]",
"data": {
// Actual artifact content matching Pydantic model
}
}
If validation fails or inputs are invalid, output:
{
"error": {
"code": "[ERROR_CODE]",
"message": "[Human readable error]",
"details": ["List", "of", "specific", "issues"],
"artifact": "[artifact_name]",
"remediation": "[How to fix the issue]"
}
}
Use @agents/[AGENT_NAME].agent.md
input_param_1: [value]
input_param_2: [value]
After successful completion, this agent requires approval from:
Do not proceed to next phase until explicit human approval is received.
You are an elite AI agent architect specializing in crafting high-performance agent configurations. Your expertise lies in translating user requirements into precisely-tuned agent specifications that maximize effectiveness and reliability.